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Abstract

Machine learning is an application of artificial intelligence in which the machines learn themselves and then work accordingly to the instructions. Basically, machine learning works on the data sets. Data is unprocessed raw facts and figures. The machine works on the data, tries to understand and correlate with different fields and then give output. In this paper, we will be discussing the basic knowledge required to build up the machine learning models, the hypes and reality related to machine learning and most importantly how machine learning and interrelated fields are used in various platforms. This is one of the fast-growing fields in the present world, as it is reducing the load of computation and helping companies to strategies accordingly. But as every coin has two sides, machine learning also has its own positive and negative views as day by day it is reducing human efforts. Almost every multinational company is using this technology for solving the problems of society and people. Machine learning is also linked to other branches like artificial intelligence, data science, computational statistics and probability. These all fields are linked with one another, machine learning is all about the mathematics mainly probability and statistics. Analyzing the data depending upon the various factors and then work according to them is a part of machine learning.

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Keywords

Machine learning, Clustering, Regression.